Principal Scientist - High sensitivity and Spatial LCMS omics

Bayer CropScience Ltd•Cambridge, MA

35d•$119,346 - $179,020•Onsite

About The Position

At Bayer we're visionaries, driven to solve the world's toughest challenges and striving for a world where 'Health for all Hunger for none' is no longer a dream, but a real possibility. We're doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining 'impossible'. There are so many reasons to join us. If you're hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there's only one choice. Principal Scientist - High sensitivity and Spatial LCMS omics Bayer has an opening for a Principal Scientist to join our Translational Sciences team for Cardiovascular, Renal, and Immunology therapeutic areas. The position is located at the Bayer Research and Innovation Center at the heart of Kendall Square in Cambridge, MA. This role is pivotal in advancing our translational research through high-sensitivity spatial LC-MS experiments in proteomics, metabolomics, and lipidomics. We seek a highly skilled scientist with extensive experience in multi-omics data generation, particularly in the context of target identification, biomarker discovery, and translation. The ideal candidate will bring deep experimental knowledge and possess the ability to collaborate effectively with cross-functional teams. This position offers a unique opportunity for a motivated individual to drive innovative research initiatives in a dynamic and collaborative environment.

Requirements

PhD in relevant fields such as chemistry, biochemistry, or biology, with 5+ years of post-graduate experience in multi-omics data generation and. raw data processing
Advanced skills and deep, hands-on experience in untargeted and targeted high-resolution LC-MS and MS analysis covering metabolomics, lipidomics, and proteomics
Expert in sample preparation for complex matrices like tissues, blood, and blood components, including spatial analysis with laser microdissection and MALDI imaging
Proven experience in completing complex scientific projects, project management and planning. You can conduct work independently as well as within a team, work collaboratively in a multidisciplinary environment
Experience in delivering target and/or biomarker-relevant insights from complex multi-omics datasets and/or targeted LC-MS and MS analysis to support the progress of drug development projects, translational activities, and understanding drugs modes of action
Proven track record of publications and presentations at scientific meetings, enabled by excellent written and oral communication skills.
Driven by curiosity, advanced science, and innovation, deploying a strong analytical, investigative, and solution-oriented mindset while being capable of completing detailed documentation of experiments and results to enable data-driven decisions.

Nice To Haves

PhD in relevant fields such as chemistry, biochemistry, or biology, with 5+ years of post-graduate experience in multi-omics data generation and raw data processing

Responsibilities

Independently design, optimize, and perform high-sensitivity and high-spatial resolution LC-MS experiments for proteomics, metabolomics, and lipidomics (multi-omics)
Prepare and process complex biological samples, e.g., biofluids for bulk analysis and tissue sections (fresh frozen or fixed) for spatial analysis / molecular imaging
Using laser microdissection technologies (LMD), prepare samples for high-resolution spatial multi-omics LC-MS analysis
Acquire proteomics/metabolomics data sets from the same limited amount of sample using nanoLC-MS instrumentation
Process raw mass-spectrometry data with diverse sets of commercial and open-source software packages to deliver high-quality results
Collaborate with data science experts and implement smooth mass-spectrometry data transfer for advanced post-processing pipelines
Summarize and present results to project team members and collaborators.